A Principal Components Analysis Biplot (or PCA Biplot for short) is a two-dimensional chart that represents the relationship between the rows and columns of a table. This article describes how to take a table with rows and columns:
And generate a Principal Component Analysis Biplot based on the table:
- Any table that contains rows and columns, including contingency tables, grids or even raw data.
- The objects that are the focus of the analysis should be in the rows of the table. For example, if analyzing brand associations, the brands should be shown in the rows.
1. Select the table that you want to use as an input to the Principal Component Analysis Biplot. For this example, we'll use a binary brand/attribute grid.
2. From the toolbar menu, select Anything > Advanced Analysis > Dimension Reduction > Principal Components Analysis Biplot.
3. From the object inspector on the right, select the table from the Input table drop-down list. If neede,d you can get the name of the input table by selecting the table and then going to Properties > General > Name in the object inspector.
4. Click the Calculate button.
The PCA biplot also allows us to see associations between the brands and attributes.